In March 2018, Citicorp launched a Facebook Messenger chatbot for its consumer banking clients in Singapore. They also plan to launch these chatbot-based services in Hong Kong and Australia later in 2018. Citicorp’s conversation-as-a-service enables customers to access account balances and credit card bill summaries. Citicorp intend to extend this capability into other areas such as wealth management services and retail banker services for selling products like cards and loans.

The Bank of Montreal has also launched a similar chatbot service initially focused on two channels: Facebook Messenger and Twitter. The deployment of chatbots is a key part of their strategy to provide an exceptional customer experience across all touch points, especially with digital as the preferred way for their customers to engage 24/7.

Process Modelling is pervasive. At the lowest level process, there is often tasks that require the knowledge worker to access Complex Knowledge in the form of documents covering regulatory, statutory, legal, tax, tariffs, policies or procedural matters. Complex Knowledge contained in documents is no longer fit for purpose for two reasons: it is difficult to use and easy to misuse.

Perception versus Reality

Organisations have stringent controls for managing these types of documents, including signatories for approving changes, with checks and balances embedded within their services, operations, risk and audit processes. The very nature of these documents is that they contain choices, pathways and outcomes. These algorithmic structures have weakened over time as permutation complexity increases. The problem has been compounded as these documents have not been subject to usability tests nor are the user decision journeys transparent and measurable.

Impact

These incomplete, ambiguous and inefficient documents have overtime led to increasing process costs, whilst negatively impacting productivity. More seriously, they have masked deep systemic nano risks, which eventually manifest themselves into unexpected exposures, brand contamination and balance sheet exposures. The irony is that most workflows have been developed separately to the choices, pathways and outcomes embedded deep within these documents, leading to an ever-bigger gap between processes and the actual knowledge work applied in practice.

Digital Transformation: Knowledge Process Re-modelling

Organisations now need to undertake Knowledge Processing Re-modelling (KPR) to simplify and streamline knowledge work. This is achieved through the deconstruction and reconstruction of documented knowledge into chatbots. The shift towards knowledge-driven (not data-driven) dialogue enables more efficient and effective user decision journeys. The captured dialogue-data is a new form of Big Data for purposes such as audit and business intelligence. Dialogue driving highly granular processes in context to choices and pathways has the potential to deliver better outcomes and change the conventions of workflow and form-filling everywhere.

]]>http://www.df2020.com/chatbot-updates/chatbots-market-update-97-week-ending-9-march-2018/feed0Chatbots – Market Update 96; week-ending 2 March 2018http://www.df2020.com/universal-thinking/chatbots-market-update-96-week-ending-2-march-2018
http://www.df2020.com/universal-thinking/chatbots-market-update-96-week-ending-2-march-2018#respondMon, 05 Mar 2018 15:13:45 +0000http://www.df2020.com/?p=2076The emergence of chatbot reality as the hyped perception starts to fade Some interesting research from multiple sources are providing lead indicators into why the future of organisations will become a blend of human and chatbot workers. More and more people are using chatbots. Some may not realise they are using chatbots as it is seemingly

]]>The emergence of chatbot reality as the hyped perception starts to fade

Some interesting research from multiple sources are providing lead indicators into why the future of organisations will become a blend of human and chatbot workers. More and more people are using chatbots. Some may not realise they are using chatbots as it is seemingly so “natural” in a digital nice way! This is especially the case through advances in chatbot voice dialogue. For example, the Smart Speaker Market being driven by Alexa, Google Assistant, Siri, Cortana and chatbots from different industries is expected to reach US$2.7bn by the end of 2018 and is expected to reach more than US$12bn by 2024. The Smart Speaker is simply just one channel, as chatbots are designed for omnichannel deployment across all digital touchpoints.

Sadly, chatbots for the past few years have been over-hyped. Exaggerated claims, especially in Natural Language Processing, have tried to claim that artificial intelligence is all knowing, aka as a
singularity. Such hype has led to a period of disillusioned as projects fail to deliver the promise. In banking, for example, some chatbot projects have failed to meet the rigours of compliance. One of the barriers is that machine learning needs to be bounded and controlled in its target area of knowledge, otherwise the learning could distort decisions, often starting in a subtle way until it eventually becomes obviously wrong.

As the reality of chatbot capabilities become better understood and delivered, more and more successes are starting to emerge. A recent study showed that 38% of consumers have had a positive
experience with a chatbot. Contrary to many experts, 48% of consumers prefer a chatbot without a personality to address their needs. In the real world, people will use a chatbot if they can get help
quickly, easily, accurately and where needed with a full dialogue audit trail.

Chatbots are a broad and deep subject. The emergent pattern is a growing portfolio of chatbot Microservices software that can be picked and mixed to deliver the right type of solution for a specific
problem. In other words, like the human world, there will be many types of chatbots, each like a subject matter expert in their own domain that co-exist with people and other chatbots. The
perception that a chatbot can do everything is simply wrong. The reality is that a portfolio of chatbots, each with their own capabilities is emerging as the right approach and will prevail.

The strategic challenge is understanding and shaping the future workforce as a blend of chatbots and people becomes inevitable to deliver value-based evolutionary change in ever decreasing time cycles.

]]>http://www.df2020.com/universal-thinking/chatbots-market-update-96-week-ending-2-march-2018/feed0Chatbots – Market Update 95; week-ending 23 February 2018http://www.df2020.com/universal-thinking/complex-knowledge-two-examples-matters
http://www.df2020.com/universal-thinking/complex-knowledge-two-examples-matters#respondMon, 26 Feb 2018 12:33:22 +0000http://www.df2020.com/?p=2053Complex Knowledge – Why it matters In the UK, there were two public disclosures within a 24-hour period, which provided more examples that Complex Knowledge in a documented form is no longer fit for purpose and is the causality of deeply rooted systemic risks. The first relates to the collapse of Carillion. The parliamentary Business

In the UK, there were two public disclosures within a 24-hour period, which provided more examples that Complex Knowledge in a documented form is no longer fit for purpose and is the causality of deeply rooted systemic risks.

The first relates to the collapse of Carillion. The parliamentary Business Committee has been cross-examining the Carillion auditors. The first surprise is that Carillion used KPMG as its external auditor and Deloittes, as its internal auditor. You would imagine this type of check and balance for strengthening the audit line of defence would be exemplary, all be it expensive. But as we have repeatedly reported, there is a material gap between perception and reality. The auditors do not check substance as it is too ‘complex’. This is particularly true for documented Complex Knowledge needed for governance and control.

Rachel Reeves, who chairs the Business Committee stated annual reports were a worthless guide to the health of the company and it was impossible to get a true sense of the assets and liabilities, which questions Carillion’s corporate governance. Wait until the Business Committee investigates below the monetary dimensions into the very fabric of documented controls and procedures!

Another area of Complex Knowledge relates to the NHS and the volume of prescription errors. A major report from the Government says such errors could be contributing to as many as 22,300 deaths a year. No wonder NHS litigations costs and pay-outs are running into billions of pounds every year, and the numbers are rising. The prescription of drugs is another area of Complex Knowledge. Though the spotlight is on the NHS, it should also on the pharmaceutical firms as their documented ‘Complex Knowledge’ for the prescription of drugs is not fit for purpose either.

Complex Knowledge is the synthesis of regulatory, statutory, legal, tax, tariffs, policies or procedural matters that are applied in practice. Surely, it is time for leadership to turn its attention to this problem though it does require a different sense-making framework to convention.

]]>http://www.df2020.com/universal-thinking/complex-knowledge-two-examples-matters/feed0Chatbots – Market Updates 94; week-ending 16 Feb 2018http://www.df2020.com/universal-thinking/chatbots-market-updates-94-week-ending-16-feb-2018
http://www.df2020.com/universal-thinking/chatbots-market-updates-94-week-ending-16-feb-2018#respondMon, 19 Feb 2018 15:38:52 +0000http://www.df2020.com/?p=2039Conduct Risk is now an epidemic and is appearing in far too many places – It is time to deal with it differently. In its simplest form, conduct risk is when an organisation’s stakeholder’s behaviour leads to unwanted behaviour or crimes, either detected or not, and detrimentally damages an organisation’s or sector’s reputation, negatively impacting

]]>Conduct Risk is now an epidemic and is appearing in far too many places – It is time to deal with it differently.

In its simplest form, conduct risk is when an organisation’s stakeholder’s behaviour leads to unwanted behaviour or crimes, either detected or not, and detrimentally damages an organisation’s or sector’s reputation, negatively impacting market stability and potentially damaging innocent individuals. Stakeholders include employees, customers, suppliers, shareholders and other connected persons.

Conduct risk by its very nature can negatively impact an organisation’s brand such as the recent case of Oxfam regarding the safeguarding scandal or the gender pay exposure from within the BBC.

Conduct risk can negatively impact a whole industry such as housing, for example the Grenfell Tower fire that has led to the Dame Judith Hackett inquiry and the recently published Interim Review of Building Regulations and Fire Safety, which stated:

“It has become clear that the whole system of regulation, covering what is written down and the way in which it is enacted in practice, is not fit for purpose…”

Conduct risk impacts multiple sectors as being witnessed by the police Operation Hydrant investigation into non-recent child sexual abuse that had received 2,094 referrals for investigation as at the end of December 2017.

Serious conduct risk once publicly exposed, tends to have some common threads. For instance, executive shock of this unexpected ‘left field’ exposure followed by the need to improve or even introduce the concept of transparency, controls and procedures.

It is apparent that as the pace of change accelerates and complexity increases, the numbers of conduct risk instances increase. Some argue this is not surprising, however, what remains surprising is the seemingly lack of new thinking and approaches that address the temptations and the resultant damaging impacts.

Conduct risk is intrinsically related to an organisation’s documented rules and ethics, which should influence the way behaviour is conducted. These documents represent complex knowledge, which has been synthesised from regulatory, statutory, legal, tax, tariffs, policies or procedural matters that need to be applied in practice.

Complex knowledge in the form of these documents, is now beginning to be perceived as not being fit for purpose because they are:

• Difficult to use and
• Easy to misuse.

This leads to the crux of the issue, which is that there is a material gap between perception and reality.

Organisations often have stringent controls for managing this type of document, including signatories for approving changes, with checks and balances embedded within their operations, risk and audit capabilities.

However, the very nature of these documents is that they contain choices, pathways and outcomes. These algorithmic structures have typically weakened over the passage of time, as risk and regulatory complexity has increased. The problem has been compounded as these documents have not been subjected to usability tests, nor are the user decision journeys transparent and measurable.

These incomplete, ambiguous and inefficient documents have led to increasing compliance and risk costs, whilst negatively impacting productivity.

Dangerously, they have masked deep systemic risks.Every choice embedded within these documents contain options. This means a user selecting the wrong option, travels along the wrong pathway, leading to the wrong outcome. The embodiment of so many choices in so many documents has led us to define the term nano risks as there are so many. It is these nano risks that seep through current controls, leading to an increasing volume of false positives and false negatives. It is the scale of these nano risks, which eventually manifest themselves into unexpected exposures, brand contamination and balance sheet exposures. The gap between perception and reality is now a chasm, which has led to spiralling compliance costs and unnecessarily high bureaucratic overheads.

These documents are produced, often not managed properly or distributed effectively, but appear everywhere.

As a reminder, the last line of defence is the external audit where applicable, who do spot checks to ensure that related documents are fit for purpose. This firmly puts the spotlight on the big four auditing firms particularly in the financial services and those that are publicly traded companies.

The personal pressures and implications now are increasing dramatically on company directors, management teams, advisors, authorised and approved persons, trustees and governors, to ensure transparency, improvement, accuracy and compliance with procedural and policy documents, are now significant and very high profile – as it should be.

Sabre Corporation has launched a Chatbot prototype powered by Artificial Intelligence, which is integrated into Microsoft’s Bot Framework and Microsoft Cognitive Services including Language Understanding Intelligent Service (LUIS).

This Chatbot prototype is a white-labelled dialogue services initially being used by Travel Services International (TSI), USA.

Chad Callaghan, Head, Sabre Studios stated:

“We are excited to start pilot testing for the bot … we believe the self-service convenience the bot offers will improve travellers’ ability to resolve routine support requests. At the same time, we are happy to help our travel agency customers ensure agents can focus on supporting more complex traveller requests. We will be interested to track how travellers learn about and interact with the bot.”

The Microsoft Botframework is an omni-channel service for Chatbots. This will be used by TSI initially using the channel Facebook Messenger providing conversation-as-a-service. The Chatbot supports:

]]>http://www.df2020.com/universal-thinking/chatbots-market-update-93-week-ending-9-february-2018/feed0Chatbots – Market Update 92; week-ending 26 January 2018http://www.df2020.com/universal-thinking/chatbots-market-update-92-week-ending-26-january-2018
http://www.df2020.com/universal-thinking/chatbots-market-update-92-week-ending-26-january-2018#respondMon, 29 Jan 2018 09:02:49 +0000http://www.df2020.com/?p=1989CHATBOTS UNDER-HYPE: THE NEW FRONTIER TO SIMPLIFY COMPLEX KNOWLEDGE PART 5 Just as a reminder, Complex Knowledge is any combination of regulatory, statutory, legal, tax, tariff, policy and procedure matter, which is primarily found within documents. Use Case: HOUSEHOLDER Planning Permission (Continued) The Competencies for creating a Chatbot Knowledge Map The competencies for the creation

]]>CHATBOTS UNDER-HYPE: THE NEW FRONTIER TO SIMPLIFY COMPLEX KNOWLEDGE PART 5

Just as a reminder, Complex Knowledge is any combination of regulatory, statutory, legal, tax, tariff, policy and procedure matter, which is primarily found within documents.

Use Case: HOUSEHOLDER Planning Permission (Continued)

The Competencies for creating a Chatbot Knowledge Map

The competencies for the creation of a Knowledge Map are based on ability to:

Synthesise complex knowledge.

Deconstruct knowledge into different subject domains.

Reconstruct the knowledge of each domain into a logic map covering each User Decision Journey re: Choices, Pathways and Outcomes.

Write clear dialogue narrative for each step.

Reduce the risks of misunderstanding by supplementing the dialogue with a picture or video.

Strategic Positioning

It is quite feasible to convert national planning regulations into a conversation-as-a-service available to citizens across the circa 360 English Government Authorities. This can be replicated across other areas of regulation especially in areas such as International Trade (beyond BREXIT), health, financial services, human resources and much more.

The result would be a portfolio of Chatbot “subject matter experts”. Each chatbot is a working and measurable knowledge asset, available 24/7 with the ability to conduct parallel conversations across all digital touchpoints.

Cost Benefits

In the case of the loft extension, the highest cost reductions could be delivered by having a national utility used by the 360 Local Authorities without each one needing to ‘reinvent the wheel’. The benefits could include:

Reduced costs of co-ordination

Reduced false positives and false negatives

Reduced overheads for governance, compliance and risks

Reduced training costs

Reduced number of appeals

Reduced litigation costs

Reduced audit costs

Reduced costs of business intelligence

Increased productivity

Shortened quality improvement cycles

New Revenue Generation

The shift from complex knowledge in content form to a conversation-as-a-service provides a fertile foundation for new value exchange and revenue generation – here are two scenarios related to this Use Case:

Scenario 1: New Conversation-as-a-Service when Planning Permission is Required

For those outcomes, which require planning permission, the service could continue to a conversation for gathering data and automation of the form filling, application letter and submission to the Local Government Authority. This would be a fee-based service offered to the citizen, thus saving them time and effort.

Scenario 2: New Conversation-as-a-Service when Planning Permitted

For those outcomes, where planning is permitted, the citizen can be offered a service whereby an agreement report is generated and filed as a smart contract (blockchain) between the Local Government Authority and the Property.

Conclusion

Complex knowledge can be made easy to use, easy to understand, no matter the complexity, and made immediately available from any digital touchpoint.

Complex knowledge can be made inclusive to everyone, no matter the language, culture or those with less abilities.

Complex knowledge can be made available for up-skilling, in the moment, empowering people to continually adapt to ever changing conditions.

Complex knowledge can be readily understood to support people making smarter choices along decision pathways to reach the best-fit outcome.

Complex knowledge can be made as a working and measurable asset, known as intangibles, enabling real-time emergent evidence to improve governance and quality, whilst shortening the cycle time for research and development.

This is a knowledge paradigm shift from monologue (content) to dialogue, which is now achievable through an ecosystem of interlinked Chatbots, each being a subject matter expert.

It is through the co-existence of Chatbots and people that revolutionises everything.

]]>http://www.df2020.com/universal-thinking/chatbots-market-update-92-week-ending-26-january-2018/feed0Press Release: DF2020 Launches new AI products to transform Complex Knowledgehttp://www.df2020.com/press-releases/df2020-launches-new-ai-products-transform-complex-knowledge
http://www.df2020.com/press-releases/df2020-launches-new-ai-products-transform-complex-knowledge#respondTue, 23 Jan 2018 08:30:13 +0000http://www.df2020.com/?p=1978“Artificial Intelligence has so much promise, but the great challenge in getting this technology broadly adopted and used to its potential is access. Currently it’s highly technical, creating a creation bottleneck. The area DF2020 focuses on is solving this issue through intuitive, visual authoring tools. This approach can democratize artificial intelligence for everyone. Very exciting.” Dr.

“Artificial Intelligence has so much promise, but the great challenge in getting this technology broadly adopted and used to its potential is access. Currently it’s highly technical, creating a creation bottleneck. The area DF2020 focuses on is solving this issue through intuitive, visual authoring tools. This approach can democratize artificial intelligence for everyone. Very exciting.” Dr. Simon Kos, Chief Medical Officer Microsoft, USA

PRESS RELEASE: TUESDAY 23RD JANUARY 2018 – Complex Knowledge contained in documents, such as; regulatory, statutory, legal, tax, tariffs, policies and procedures, is no longer fit for purpose, as it is difficult to use and easy to misuse. This is a huge problem affecting every person and organisation worldwide.

Df2020 has launched Chatbot Author for democratising end-users so they are empowered to create, share, measure and evolve chatbots. Once deployed, these chatbots simplify and streamline the use of Complex Knowledge for employees, customers, suppliers and citizens.

John Rawlings, Co-Founder and CEO commented, “Our every-day lives are affected by Complex Knowledge especially in the health, public, and financial service sectors. The cost of not following procedures is unthinkable. Yet for such a fundamental practise, we are still using inefficient and often outdated methods. The use of Chatbot Technology means that we can now make knowledge easy to use, easy to understand and available to virtually everybody from any digital touchpoint.”

Chatbot Author is now available worldwide from the Windows 10 Store and Business store with products ranging from £29.99 to £199.99 subscription per month, or the equivalent in the local currency. End-users can construct Knowledge Maps to automatically generate Chatbots, without the need for software engineers. The Chatbots are seamlessly linked with the Client’s Azure Botframework for deployment across 14+ channels. This means the Chatbots can be made available privately or publicly through the web, mobile or social networks.

This new form of white-box artificial intelligence offers organisations better control, deep transparency and smarter management of nano-risks typically found deep within the documents of Complex Knowledge. The captured dialogue-data is used for compliance, conversational insights and knowledge learnings at the edge.

Freddie McMahon, Co-Founder and Chatbot Thought Leader concluded, “The ability for organisations to grow portfolios of working and measurable knowledge assets is a new growth area designed for the mushrooming intangible economy. We have reversed 50 years of technology thinking from data-driven to knowledge-driven. This collapses the time to deliver socioeconomic value locally, nationally and globally by deploying conversation-as-a-service”.

“This approach, stunning in its simplicity and revolutionary in its aspiration, will help transform the generation and delivery of expertise in ways that I have dreamt of for years!” Merlin Stone, Professor of Marketing and Strategy, School of Management and Social Sciences, St Mary’s University, Twickenham, UK

]]>http://www.df2020.com/press-releases/df2020-launches-new-ai-products-transform-complex-knowledge/feed0Chatbots – Market Update 91; week-ending 19 January 2018http://www.df2020.com/chatbot-updates/chatbots-market-update-91-week-ending-12-january-2018
http://www.df2020.com/chatbot-updates/chatbots-market-update-91-week-ending-12-january-2018#respondMon, 22 Jan 2018 14:45:12 +0000http://www.df2020.com/?p=1975Commonwealth Bank of Australia has launched a chatbot for conversation-as-a-service with its customers for supporting over 200 different types of banking tasks. Their Chatbot is called Ceba, which has been trained to handle over 60,000 different ways customers ask for support such as for activating their card, checking account balance, making payments or getting cardless

]]>Commonwealth Bank of Australia has launched a chatbot for conversation-as-a-service with its customers for supporting over 200 different types of banking tasks. Their Chatbot is called Ceba, which has been trained to handle over 60,000 different ways customers ask for support such as for activating their card, checking account balance, making payments or getting cardless cash. Ceba is a new generation of bank teller that is available 24/7 and handles parallel conversations.

The conversation-as-a-service is currently supporting some customers with the intention of a roll-out to support over 6 million customers. The dialogue uses the three modes of conversation: type, tap and talk.

]]>http://www.df2020.com/chatbot-updates/chatbots-market-update-91-week-ending-12-january-2018/feed0Chatbots – Market Update 90; week-ending 12 January 2018http://www.df2020.com/universal-thinking/chatbots-under-hype-the-new-frontier-to-simplify-complex-knowledge-part-4
http://www.df2020.com/universal-thinking/chatbots-under-hype-the-new-frontier-to-simplify-complex-knowledge-part-4#respondMon, 15 Jan 2018 12:47:54 +0000http://www.df2020.com/?p=1942CHATBOTS UNDER-HYPE: THE NEW FRONTIER TO SIMPLIFY COMPLEX KNOWLEDGE PART 4 Just as a reminder, Complex Knowledge is any combination of regulatory, statutory, legal, tax, tariff, policy and procedure matter, which is primarily found within documents. Use Case: HOUSEHOLDER Planning Permission (continued) Creating the Knowledge Map and Chatbot The Knowledge Map is a symbolic

]]>CHATBOTS UNDER-HYPE: THE NEW FRONTIER TO SIMPLIFY COMPLEX KNOWLEDGE PART 4

Just as a reminder, Complex Knowledge is any combination of regulatory, statutory, legal, tax, tariff, policy and procedure matter, which is primarily found within documents.

Use Case: HOUSEHOLDER Planning Permission (continued)

Creating the Knowledge Map and Chatbot

The Knowledge Map is a symbolic algorithm based upon Choices, Pathways and Outcomes. By its very nature, the edge of a Knowledge Map, which establishes its boundaries, are defined by each Pathway’s end-points. An end-point is either an Outcome or a Link to another Knowledge Map.

Each Symbol within a Knowledge Map defines the type of Dialogue Operation such as Choice, Pathway, Outcome or Note. Within each Symbol there are Properties that contain the Dialogue Script. This Script maybe complemented by an in-line Dialogue Picture of Video.

As previously explained, a Picture can be used to improve the precision of a Decision.

The Video can be used for Just-in-Time training in the context of a given Dialogue-Step. This poses an interesting question of when is an expert not an expert. The answer is when they come across a Dialogue-Step whereby they do not have familiarity of the contextual knowledge. The in-dialogue video is only triggered by the person and therefore is not used when there is familiarity.

The Knowledge Map has some embedded rules such as all the Symbols need to be connected and that all of the Pathways end with an Outcome or Link.

Once the Knowledge Map is completed the Chatbot can be created through various techniques such as writing software code or through an automation process.

In terms of the Loft Extension the following Knowledge Map profile emerged:

42 Symbols

16 Choice Symbols with

36 Decision Options

Planning Permission Required = 9 Outcomes, each with a different reason

Planning Not Permitted = 4 Outcomes, each with a different reason

Planning Permitted = 3 Outcomes, each with a different reason

Converted Buildings = 1 Outcome (outside scope)

Flats / Maisonettes = 1 Outcome (outside scope)

Other Buildings = 1 Outcome (outside scope)

It is worth comparing this type of profile data to the ‘original source’ where such data is non-existent as the Complex Knowledge is in the form of ‘dense’ documentation.

Testing the Chatbot

Once the Chatbot is completed, the testing can commence. It is important to ensure the logic and narrative accurately reflects the ‘original source’ of the Complex Knowledge. But, let’s go back to the status quo. The ‘original source’ of the Complex Knowledge is a document. In this case, it consisted of two national documents: the regulation and the guidelines for understanding the regulations. None of these documents were subjected to usability tests. As this is the de facto standard, it is no surprise the Complex Knowledge in documented form is:

“difficult to use and easy to misuse”

In terms of testing, one important consideration is the clarity of the dialogue during the User Decision Journey. A universal benchmark is that the dialogue can be read, understood and moved on within eight seconds. Experience has shown that the number of characters, including spaces, within a Dialogue-Step should be no more than 300. Enforcement of this limit enables the Complex Knowledge to be deconstructed and reconstructed into small simple steps, no matter the complexity of the subject.

Masking Complexity

The User Decision Journey is through the interaction with the Chatbot using a Conversational User Interface, which can be voice or text. The user does not see the Knowledge Map as the interaction is in context to the User Decision Journey. In terms of outliers, the shortest and the longest User Decision Journey can be measured in terms of the universal benchmark of 8 seconds per Dialogue-Step, which is the typical Attention Span. Thus, the following benchmarks could be established in context to the Loft Extension advice:

Shortest User Decision Journey

Number of Dialogue-Steps: 3

Duration: 24 Seconds

Outcome: Planning Permission Required

Longest User Decision Journey

Number of Dialogue-Steps: 19

Duration: 2.5 minutes

Outcome: Planning Permitted

The implications of masking complexity are quite profound. The ability to mask complexity and include JIT training provides the basis for up-skilling and down-skilling, whilst spreading the ability for more and more people to self-manage inside and outside the organisation.